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Social determinants of health (SDoH) impact psychiatric conditions. Routinely collected health data are frequently used to evaluate important psychiatric clinical and health services outcomes. This study explored how key SDoH are used in psychiatric research employing routinely collected health data.A search was conducted in PubMed for English-language articles published in 2019 that used routinely collected health data to study psychiatric conditions. Studies (n = 19,513) were randomly ordered for title/abstract review; the first 150 meeting criteria progressed to full-text review. Three key SDoH categories were assessed: (1) gender and sex, (2) race and ethnicity, and (3) socioeconomic status. Within each category, data were extracted on how variables were included, defined, and used in study design and analysis.All studies (n = 103) reported on at least one of the key SDoH variables; 102 (99.0%) studies included a gender and/or sex variable, 30 (29.1%) included a race and/or ethnicity variable, and 55 (53.4%) included a socioeconomic status variable. No studies explicitly differentiated between gender and sex, and SDoH were often defined only as binary variables. SDoH were used to define the target population in 14 (13.6%) studies. Within analysis, SDoH were most often included as confounders (n = 65, 63.1%), exposures or predictors (n = 23, 22.3%), and effect modifiers (n = 14, 13.6%). Only 21 studies (20.4%) disaggregated results by SDoH and 7 (6.8%) considered intersections between SDoH.Results suggest improvements are needed in how key SDoH are used in routinely collected health data-based psychiatric research, to ensure relevance to diverse populations and improve equity-oriented research.

Maternal schizophrenia is associated with adverse birth outcomes, but the reasons for this remain unclear. In a population-based cohort of infants born to women with schizophrenia, we determined the occurrence of key perinatal outcomes and explored whether factors identifiable in our datasets explained any elevated risk. Using population-level health administrative data linked to clinical birth-registry data in Ontario, Canada (2006–2011), we examined the relative risk (RR) of preterm birth (

Psychiatric readmission is a common negative outcome. Predictors of readmission may differ by sex. This study aimed to derive and internally validate sex-specific models to predict 30-day psychiatric readmission. We used population-level health administrative data to identify predictors of 30-day psychiatric readmission among women (n = 33,353) and men (n = 32,436) discharged from all psychiatric units in Ontario, Canada (2008–2011). Predictor variables included sociodemographics, health service utilization, and clinical characteristics. Using derivation data sets, multivariable logistic regression models were fit to determine optimal predictive models for each sex separately. Results were presented as adjusted odds ratios (aORs) and 95% confidence intervals (CI). The multivariable models were then applied in the internal validation data sets. The 30-day readmission rates were 9.3% (women) and 9.1% (men). Many predictors were consistent between women and men. For women only, personality disorder (aOR 1.21, 95% CI 1.03–1.42) and positive symptom score (aOR 1.41, 95% CI 1.09–1.82 for score of 1 vs. 0; aOR 1.44, 95% CI 1.26–1.64 for ≥ 2 vs. 0) increased odds of readmission. For men only, self-care problems at admission (aOR 1.20, 95% CI 1.06–1.36) and discharge (aOR 1.44, 95% CI 1.26–1.64 for score of 1 vs. 0; aOR 1.79, 95% CI 1.17–2.74 for 2 vs. 0), and mild anxiety rating (score of 1 vs. 0: aOR 1.30, 95% CI 1.02–1.64, derivation model only) increased odds of readmission. Models had moderate discriminative ability in derivation and internal validation samples for both sexes (c-statistics 0.64–0.65). Certain key predictors of psychiatric readmission differ by sex. This knowledge may help to reduce psychiatric hospital readmission rates by focusing interventions.